UC San Diego

Throughout the course of evolution, almost all organisms have generated complex, hierarchical, and robust regulatory systems. One major component of these biological regulatory systems is the transcriptional activation or repression of gene expression. This regulation is carried out simultaneously across a genome by thousands of biological components at thousands of individual promoters. The sum total of all of the regulatory events and their interconnections or overlaps is commonly referred to as the transcriptional regulatory network. The focus of this thesis is to determine the mechanisms or guiding principles behind these transcriptional regulatory networks and to provide a basis upon which predictive mathematical models of these networks can be built. In the first section, a reconstruction of the full transcriptional regulatory network for a model organism is presented along with the OME software framework developed to handle the full complexity of genome-scale datasets and models. In the second section, the mechanisms of individual regulatory events are elucidated in a massively parallel fashion using ChIP- exonuclease and the OME framework. This leads to fundamental insights into the nature of transcriptional initiation complexes for canonical regulators. Finally, in the third section, an effort is undertaken to determine systems level mechanisms which dictate the coordinate regulation of hundreds of simultaneous regulatory events in response to major physiological and metabolic perturbations. Here we show that the two principal dimensions of a metabolic system, growth and the production of energy, drive not only the organization of the metabolic network, but also the organization of the transcriptional regulatory network